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» Combined Gene Selection Methods for Microarray Data Analysis
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CVPR
2004
IEEE
16 years 5 months ago
Feature Selection for Classifying High-Dimensional Numerical Data
Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
Yimin Wu, Aidong Zhang
112
Voted
WABI
2004
Springer
132views Bioinformatics» more  WABI 2004»
15 years 8 months ago
Joint Analysis of DNA Copy Numbers and Gene Expression Levels
Abstract. Genomic instabilities, amplifications, deletions and translocations are often observed in tumor cells. In the process of cancer pathogenesis cells acquire multiple genom...
Doron Lipson, Amir Ben-Dor, Elinor Dehan, Zohar Ya...
BMCBI
2005
201views more  BMCBI 2005»
15 years 2 months ago
Principal component analysis for predicting transcription-factor binding motifs from array-derived data
Background: The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to...
Yunlong Liu, Matthew P. Vincenti, Hiroki Yokota
130
Voted
BMCBI
2007
197views more  BMCBI 2007»
15 years 3 months ago
Boolean networks using the chi-square test for inferring large-scale gene regulatory networks
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Haseong Kim, Jae K. Lee, Taesung Park
BMCBI
2008
157views more  BMCBI 2008»
15 years 3 months ago
Dimension reduction with redundant gene elimination for tumor classification
Background: Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DN...
Xue-Qiang Zeng, Guo-Zheng Li, Jack Y. Yang, Mary Q...